AI-Driven Sanctions Case: Transforming Compliance Speed, Accuracy & Governance

A leading RegTech innovator specializing in financial crime prevention and compliance automation. The organization supports global financial institutions facing rapidly evolving regulatory requirements and the operational burden of sanctions screening, AML processes, and continuously expanding global watchlists.

Global financial institutions are under mounting pressure as sanctions lists continue to expand beyond 20,000 active designations worldwide. Traditional sanctions review processes rely heavily on manual alert adjudication, leading to inefficiencies, high operational costs, and increased exposure to human error. As regulatory expectations intensified, the client recognized the need to modernize its sanctions processing capabilities to accelerate adjudication speed, improve precision while reducing false positives, ensure transparent and regulator-aligned auditability, and maintain strong governance across BSA/AML, SR 11-7, OCC, and global compliance frameworks. The overarching objective was to create a scalable, AI-driven sanctions workflow that preserved human oversight and enterprise-grade controls.

OMI engineered a next-generation sanctions clearing platform built on an agentic AI architecture designed specifically for regulated compliance environments. At the core of the solution were Domain Agent Models (DAMs,) specialized, explainable AI agents trained on sanctions adjudication and compliance logic. These agents operated within a tightly governed framework powered by Policy-as-Code (PaC) and GenAIOps, ensuring consistent decisioning, auditability, and regulatory alignment.

The platform incorporated human-in-the-loop controls that automatically escalated high-risk or ambiguous alerts to compliance experts, while low-risk alerts were cleared autonomously to reduce manual workload and allow teams to focus on complex cases. Explainable AI capabilities provided transparent, regulator-ready reasoning with immutable audit logs, supporting examination and validation requirements. The solution also included real-time sanctions data synchronization, enabling continuous ingestion of updates from OFAC, the EU, FCDO, and UBO sources.

From a technical standpoint, the implementation leveraged a robust architecture built on a Python (Flask) application layer, Strands Agents with LiteLLM models, compliance-ready retrieval-augmented generation (RAG) grounding, dynamic prompt orchestration, and comprehensive GenAIOps monitoring with versioning and rollback controls. Together, these components delivered a trustworthy, scalable, and governance-aligned AI platform suitable for enterprise-wide adoption.

The AI-driven sanctions platform delivered significant and measurable business impact. Adjudication cycles accelerated by up to 300×, while false positives were reduced by 60 percent and overall case resolution times improved by 75 percent. The automation of low-risk alert handling led to a 40 percent reduction in manual labor costs, without compromising regulatory rigor. In addition to performance gains, the client achieved regulator-compliant audit logs with full explainability and established a closed-loop governance model that integrated automation, human oversight, transparency, and continuous improvement, creating a sustainable operational advantage.